GetAFreelancer.com - Data Mining From Digg (by script)

Data Mining From Digg (by script)

Data Mining From Digg (by script) is project number 324462 posted at GetAFreelancer.com. Click here to post your own project.

Status: Closed (Selected Service Provider)

Selected Providers: selected service provider andreiandrei

Budget: $30-250

Created: 10/04/2008 at 17:37 EDT

Bidding Ends: 10/07/2008 at 17:37 EDT

Project Creator: yoavf
Buyer Rating:
(4 reviews)

Description: Data Mining Task from Digg

You'll be supplied with a list of movie titles.
Your task is to gather the following data

- List of Digg Submissions related to the movie based on the following search terms:

a. search for ||movie_name movie||
b. search for ||movie_name film||
c. search for ||movie_name trailer||
d. search for ||movie_name watch||
e. search for ||movie_name see||

IE for the movie "The Eye" you will run the following separates searches
"The Eye movie"
"The Eye film"
"The Eye Trailer"
"The Eye watch"
"The Eye see"
All *without* the double quotes!!

All searches should be combined and duplicates deleted (delete only exact duplicates, that leads to the same digg submission, not the same external URL)!

Digg search settings: "Title, Description, and URL", "All Stories". "Including burried: NO"

The results should be saved in a table (preferably excel, CSV is also possible) with the following data

ID (auto increment Serial Number), Date Submitted (dd/mm/yyyy), Title, Full URL of DIGG Item, FULL URL ITEM IS LINKED TO, number of diggs, number of comments, Made Popular(YES/NO)

Please note that the date appears on digg as a relative date (ie 2 years 34 days ago). This should of course be converted to the exact data).

Made Popular: Regular diggs (not popular) shows the following text on search result: "username" submitted "342 days ago"
Popular items shows the following text instead: "Username" made popular "342 days ago"

Sample data attached. Please make sure you understand the requirements before posting your bid.

I expect this to be done, as accurately as possible by script (automatically) and in 2-3 days.

Job Type:
Data Processing
Market Research
Python
Ruby/Ruby on Rails

Database: (None)

Operating system: (None)

Bid count: 17

Average bid: N/A

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